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Title

A preliminary study on the prediction of human protein functions

Authors
Pagni, Marco
Published in Ferrandez, J.M. Foundations on Natural and Artificial Computation: 4th International Work-conference on the Interplay Between Natural and Artificial Computation, IWINAC 2011. Heidelberg: Springer. 2011, p. 334-343
Collection Lecture Notes in Computer Science; 6686
Abstract In the human proteome, about 5’000 proteins lack experimentally validated functional information. In this work we propose to tackle the problem of human protein function prediction by three distinct supervised learning schemes: one-versus-all classification; tournament learning; multi-label learning. Target values of supervised learning models are represented by the nodes of a subset of the Gene Ontology, which is widely used as a benchmark for functional prediction. With an independent dataset including very difficult cases the recall measure reached a reasonable performance for the first 50 ranked predictions, on average; however, average precision was quite low.
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ISBN: 978-3-642-21343-4
Full text
Book chapter (Published version) (17.4 MB) - document accessible for UNIGE members only Limited access to UNIGE
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Research group Calipho (80)
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(ISO format)
BOLOGNA, Guido et al. A preliminary study on the prediction of human protein functions. In: Ferrandez, J.M. (Ed.). Foundations on Natural and Artificial Computation: 4th International Work-conference on the Interplay Between Natural and Artificial Computation, IWINAC 2011. Heidelberg : Springer, 2011. p. 334-343. (Lecture Notes in Computer Science; 6686) https://archive-ouverte.unige.ch/unige:108944

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Deposited on : 2018-10-09

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